Full Terms & Conditions of access and use can be found athttp://www.tandfonline.com/action/journalInformation?journalCode=rjpr20

Journal of Property Research

ISSN: 0959-9916 (Print) 1466-4453 (Online) Journal homepage: http://www.tandfonline.com/loi/rjpr20

High-impact information types on market value:property appraisers’ information sources andassessment confidence

Lina Bellman

To cite this article: Lina Bellman (2018): High-impact information types on market value: propertyappraisers’ information sources and assessment confidence, Journal of Property Research, DOI:10.1080/09599916.2018.1443152

To link to this article: https://doi.org/10.1080/09599916.2018.1443152

© 2018 The Author(s). Published by InformaUK Limited, trading as Taylor & FrancisGroup

Published online: 28 Feb 2018.

Submit your article to this journal

View related articles

View Crossmark data

Journal of ProPerty research, 2018https://doi.org/10.1080/09599916.2018.1443152

High-impact information types on market value: property appraisers’ information sources and assessment confidence

Lina Bellman 

Department of Business, economics and law, centre for research on economic relations, Mid sweden university, sundsvall, sweden

ABSTRACTThis explanatory paper describes and analyses which types of information professional property appraisers perceive to have the most impact on a commercial property’s estimated market value, which information sources they primarily use, and how reliable they perceive the information sources to be. The paper also investigates whether appraisers’ perceptions differ depending on the location of the business. A sample of 67 authorised property appraisers in Sweden was surveyed using the repertory grid technique as a questionnaire tool (to investigate unconscious behaviour), and non-parametric statistics. Analyses of the data show that four types of information have the greatest impact on estimated market value: the local environment and location are perceived as reliable, and property appraisers have confidence in those assessments; rental income seems problematic, because the property owner is the major source of information; and property appraisers are not confident in assessments based on discount rates. This pattern holds for various geographical locations.

1. Introduction

The appraisal process can be described as a function of information (Gallimore, 1996). Property appraisers gather, analyse, interpret and assess various kinds of information from different sources to estimate the value of commercial property (Tidwell & Gallimore, 2014).

Because property appraisal is by nature an approximation, the process is affected by uncer-tainties. According to French and Gabrielli (2005), uncertainties in available information about both the property market and the property object affect the estimated value of a specific property object regardless of the valuation model used. Öhman, Söderberg, and Uhlin (2012) point to a lack of research on assessments of various types of information used in valuation models at the property object level. Bellman and Öhman (2016) also call for studies of how professional property appraisers rank the importance of various information types for assessing commercial properties. Behavioural research may help by capturing appraisers’ unconscious

KEYWORDSassessment of information; behavioural research; commercial properties; information sources; property appraisers

ARTICLE HISTORYreceived 7 august 2017 accepted 15 february 2018

© 2018 the author(s). Published by Informa uK limited, trading as taylor & francis Group.this is an open access article distributed under the terms of the creative commons attribution-noncommercial-noDerivatives license (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.

CONTACT lina Bellman lina.bellman@miun.se

OPEN ACCESS

2 L. BELLMAN

thinking – what is going on ‘inside their minds’. Traditional surveys, which often measure responses on scales suitable to statistical analyses, fail to measure what appraisers believe about what they think and do (Klamer, Bakker, & Gruis, 2017). The repertory grid technique may provide more genuine answers about appraisers’ inner thoughts (cf. Kelly, 1955).

Property appraisers’ lack of confidence in appraised values is related to uncertainties at the property market level (Tidwell & Gallimore, 2014). For example, behavioural studies have found that property appraisers who work in unfamiliar markets anchor their valuations on anonymous experts’ opinions (Diaz & Hansz, 1997, 2001), but this anchor behaviour is not found in familiar markets (Diaz, 1997). Diaz and Hansz suggest that when property appraisers experience increased uncertainty, they use information they would not normally consider reliable. According to Levy and Schuck (1999) and Baffour Awuah and Gyamfi-Yeboah (2017), lack of reliable data increases the probability of errors in the valuation statement.

Lack of reliable data also increases the risk of client influence. Several studies have inves-tigated client impact on property appraisers’ value estimates (e.g. Amidu, Aluko, & Hansz, 2008; Bellman & Öhman, 2016; Kinnard, Lenk, & Worzala, 1997; Levy & Schuck, 1999, 2005; Mwasumbi, 2016; Nwuba, Egwuatu, & Salawu, 2015). According to Levy and Schuck (2005), clients can have a central position and affect property appraisers in several ways, including through the information they supply. Property valuation may be problematic if appraisers depend on client supplied information that may be both uncertain and important in estimating the value.

Previous research (Diaz, Gallimore, & Levy, 2002, 2004; Hordijk, Nelisse, & Koerhuis-Gritter, 2011) demonstrated that property appraisers’ performance differed in various geo-graphical settings such as different counties. For example, Hordijk et al. (2011) showed that information sources and information reliability differed among valuation practices in France, Germany, Italy, The Netherlands, Portugal, Russia, Spain and the UK. Differences have also been found between territories with a high degree of autonomy. Lim, Adair, McGreal, and Webb (2006) found evidence of significant differences between professional property appraisers in Hong Kong and mainland China. (In 1997, Hong Kong became a special administrative region of China with a high degree of autonomy). Those differences are found in both appraisal behaviour and the information used to perform appraisals.

The purpose of this paper is to investigate which types of information professional prop-erty appraisers perceive to have the most impact on a commercial property’s estimated market value. The paper also focuses on the sources from which this information is gathered and how property appraisers perceive the reliability of the information (i.e. their assessment confidence), and investigates whether there are differences in the use of information types depending on geographical location.

The current study uses Swedish data. The Swedish property market, with a public land registry of individual data on domestic properties and consistently applied laws and regu-lations to uphold private property rights, is internationally recognised as transparent (Jones LaSalle Global Real Estate Transparency Index, 2016). Like some other countries, Sweden has no rental or operational cost indices, and its commercial property contracts are not publicly accessible (Englund, Gunnelin, Hoesli, & Soderberg, 2004). However, such data may be supplied by consultant companies and definitions of operational costs and their components are presented, for example, in the IPD/SFI Tutorial for valuation. According to Englund et al. (2004), information that is accessible to the public is often produced by

JOURNAL OF PROPERTY RESEARCH 3

property consultant companies and often based on incomplete data. Lind and Lundström (2009) argue that consulting firms’ reports are used by appraisers as reliable sources of information, which may bias property valuations since the information may be based on unjustified assumptions.

Swedish commercial lease contracts differ from those in other European property mar-kets in several ways: Swedish property owners provide operation and maintenance as part of the total rent; Swedish office leases are short term, and most contracts are written according to a standard template (Nordlund & Lundström, 2011). In the international context, the Swedish property market is relatively small. Nordlund and Lundström (2011) estimate the average transaction volume of commercial properties at 100 billion SEK per year, equivalent to an annual turnover of 10% of the commercial property portfolio’s market value.

Local commercial property markets vary in overall value and in number of transactions. Of Sweden’s commercial properties, 50% are in Stockholm (the capital of Sweden), 25% in the County of Västra Götaland (including Gothenburg, Sweden’s second largest city) and the County of Skåne (including Malmoe, the third largest city), and the remaining 25% in the rest of Sweden. The type of owner also differs between areas (NAI Svefa, 2017; Nordlund & Lundström, 2011). In Stockholm, commercial property owners are primarily institutional, while in Malmoe many owners are private. There is a mix of owners in Gothenburg, many of them municipal. Englund et al. (2004) argue that rental forecasts may differ among Stockholm, Gothenburg and Malmoe because Stockholm is a more sophisticated market with a larger proportion of institutional investors. Regional differences in market volume and property owners may influence the market segments’ transparency and create differ-ences in the availability of information. Crosby, Devaney, Lizieri, and McAllister (2018, p. 657) state that ‘thin trading in real estate markets typically results in poor information flows, which vary over time and among market segments’. Property appraisers in smaller markets may normally have less access to public and market information. Therefore, different infor-mation sources may be available in smaller market segments than in larger market segments.

Swedish property appraisers are authorised by the non-political, non-profit organisation, Samhällsbyggarna (‘Swedish Professionals for the Built Environment’) and are assumed to follow the organisation’s code of ethics and valuation principles (Lundström, 2005). The organisation is intended to produce qualified appraisers who can undertake prop-erty valuations for various clients without question. Independence is one of four basic requirements in the organisation’s statutes for the general authorisation of an appraiser of commercial properties. Most authorised Swedish property appraisers tend to use the discounted cash flow method (McParland, Adair, & McGreal, 2002), which is appropriate for calculating market values for financial statements or annual accounts (Nordlund, 2008). Findings from Nordlund (2008) also suggest that Swedish property appraisers have three fundamental inputs when using the discounted cash flow method: estimated net operating income (NOI), value at the end of the time horizon (normally 5 or 10 years) and discount rate (see also Lind & Nordlund, 2014). The estimated NOI can be defined as future rental income (adjusted by vacancy rates and other losses) minus operating, maintenance and related expenses (Öhman et al., 2012).

The Swedish commercial property market is an appropriate empirical base because of its transparency, including solid property rights, public land registry and authorised profes-sional property appraisers. The Swedish commercial property market comprises a handful of local markets with different transaction volumes and types of domestic property owners.

4 L. BELLMAN

Unlike markets in many other countries, Sweden’s domestic commercial property market was not greatly affected by the global financial crises (Nordlund & Lundström, 2011). The Swedish economy rapidly recovered from the crises, and at the time of data collection the Swedish commercial property market was relatively normal.

The rest of the paper is organised as follows: Section 2 describes the theoretical frame-work. Section 3 outlines the sample, data, and statistical techniques used, and is followed by Section 4, in which the empirical findings are analysed. The concluding Section 5 ends the paper by considering conclusions, implications, limitations and suggestions for further research.

2. Frame of reference

2.1. Theory of search and theory of choice: impact on estimated market value

Behavioural property research can be divided into various research streams or even catego-ries, such as deviations from the normative appraisal process, comparable sale selections, appraisal biases and feedback (Black, Brown, Diaz, Gibler, & Grissom, 2003; Diaz & Hansz, 2007). These categories are partly interrelated as they all are related to information.

During the appraisal process, property appraisers gather, analyse and interpret a large amount of information considered relevant to assess a property’s estimated market value. The process can therefore be seen as a decision-making process consisting of a ‘theory of search’ and a ‘theory of choice’ (Cyert & March, 1963, p. 10). Theory of search concerns property appraisers’ decisions about which information sources to use. Theory of choice concerns their assessment of the selected information, resulting in an estimated market value (cf. Stabell, 1978). Notably, the choice of information sources can greatly affect the output, and property appraisers can move back and forth between the two decision steps in the appraisal process. Figure 1 demonstrates a simplified appraisal process.

The arrows in Figure 1 illustrate that the information flow is the ‘artery’ in the appraisal process, where input has a direct effect on output. For annual statements, estimated mar-ket value is approximately equivalent to fair value, defined by the International Valuation Standards Committee (2013) as

the estimated amount for which an asset or liability should exchange on the valuation date between a willing buyer and a willing seller in an arm’s length transaction, after proper market-ing and where the parties had each acted knowledgeably, prudently and without compulsion.

Regardless of the valuation method (e.g. sales comparison, income/capitalisation or discounted cash flow), different types of property- and market-specific information such as rental income, investments in the property, operating and maintenance costs, residual value, and cost of capital may have different impacts on estimated market values (Nordlund, 2008). Bellman and Öhman (2016) compiled information types from previous research (e.g.

Figure 1. Decision steps and information flows in the property appraisal process.

JOURNAL OF PROPERTY RESEARCH 5

Geltner, Miller, Clayton, & Eichholtz, 2007; Netzell, 2009; Nordlund, 2010) and interviews. These information types can all be related to estimations of the market value. One of the information types – rental income – includes historical, current and forecasted levels of income related to rents, leases and interest payments. The contractual terms of leases include the duration of the rental agreement and termination conditions. Vacancy rate includes cur-rent and projected vacant rentable areas. Location, of course, is a well-known information type in property valuation, related to features of the property’s local environment, such as transportation, type of housing, neighbours and tenants. Information on condition and standards includes the age of buildings and refurbishments.

According to Bellman and Öhman (2016), the information type ‘discount rate’, cal-culated on general societal and other more specific objects, captures the actual cost of the property’s equity, return and risk. The residual value is the value remaining after the property’s estimated economic life. Operating costs are typically utilities such as electricity and heating, and maintenance costs are incurred to preserve and extend the property’s technical life. Investment needs include urgent maintenance, improvements, modifications and performance enhancements. Other cost-related information types are administration/management and environmental pollution. Like operating and maintenance costs, manage-ment and administration costs depend on whether the function is in-house or outsourced. Environmental pollution costs may be incurred in properties with negative environmental impacts.

There will always be an uncertainty in the information used as input, and this uncer-tainty will transfer to the output (French & Gabrielli, 2005). This suggests that various types of information have different effects on property appraisals and on estimates of property objects’ market values. Nordlund’s (2008) interview study shows that in valuation calcu-lations Swedish property appraisers often use standardised inputs of market rent levels, vacancy rates, and operating and maintenance costs. Lind and Lundström (2009) highlight this use of standardised assumptions instead of object-specific information and further point out appraisers’ underestimates of operating and maintenance expenses and vacancy rates. When Öhman et al. (2012) compared appraisers’ forecasted NOI with figures reported in company income statements, they found systematic overestimation of NOI and suggested, in line with Lind and Lundström (2009), that this is due to overestimates of rental revenue and underestimates of operating and maintenance expenses and vacancy rates. Nordlund (2008) also indicates that Swedish appraisers often extract the discount rate directly from transactions in the market (comparable sales).

2.2. First decision: Information sources to use

The first step in the simplified appraisal process outline in Figure 1 is the decision about which information sources to use. Appraisers collect property-specific information directly from the property object and the property market. They visually inspect the property and gather data about it and the property market from their own and/or branch-specific data-bases and property indices.

Uncertainty in the appraisal process exists as early as the gathering stage. ‘Uncertainty is due to the lack of knowledge and poor or imperfect information about all the inputs that can be used in the valuation’ according to French and Gabrielli (2005, p. 81). They continue,

6 L. BELLMAN

‘If there is sufficient market evidence, the property appraiser will feel more certain of the market conditions’, while less market information will increase their uncertainty.

Types of information that can affect appraisal uncertainty are related to both the prop-erty object and the property market. Although most studies (e.g. French & Gabrielli, 2004; Tidwell & Gallimore, 2014) highlight inherent market uncertainty, some also include uncer-tainty in the property object itself. In Joslin, 2005 UK study, commercial property appraisers asserted the presence of uncertainty during the appraisal process. Uncertainty related to the property object was implicit in the object and its basic qualities such as condition, location and future plans for local development; uncertainty in the property market was implicit in current and future market conditions and in the ability of appraisers to observe market changes. Uncertainty was also related to the quantity and quality of available information and the appraiser’s (lack of) experience working with comparable evidence.

Clients (property owners) may provide a wide range of private information about the property and its local market to property appraisers (Levy & Schuck, 2005), including rental information (e.g. rental income, contractual term of leases and vacancy rates); the property’s condition and standards; its location and local environment, and costs (e.g. administration, management and operating costs). Property owners have an information advantage because they hold property- and/or market-specific information that can affect the appraisal and that they can provide to the property appraiser directly or indirectly (Levy & Schuck, 1999, 2005).

The client’s role as an information provider is contradictory. Clients have the incentive of quality assurance to provide external market participants with accurate valuations and market credibility and thus may assist the property appraiser by providing information about the object or the market of which the property appraiser may be unaware (Crosby, Lizieri, & McAllister, 2010; Gallimore, 1996). However, clients also have an economic incentive to act in their own self-interest (Levy & Schuck, 1999, 2005). Depending on the purpose of the appraisal (for use as collateral for obtaining credit or preparing annual accounts), clients may want a higher or lower estimate of the property’s value. Previous research (Chen & Yu, 2009; Levy & Schuck, 1999, 2005) suggests that clients have ‘information power’, meaning that their information can bias the appraisal. Levy and Schuck (2005) distinguish between information power and expert power as means of influence by defining information power as clients’ control over information relevant to valuations and expert power as clients’ expertise in property and the practice of valuation. Those two are difficult to distinguish because they are interconnected through property owners’ unique knowledge and information about the property object and the local market.

Figure 2 summarises information sources and information flows. On the right side of the figure, direct information flows from the property object and the property market to the appraiser; on the left, indirect information flows from the property object and the property market, via the property owner, to the property appraiser. This demonstrates the role property owners can play as information providers, which can lead to conscious or unconscious client influence.

Although several types of information, including the basic qualities of the property object and comparable properties have more or less impact on the appraisal process and the property’s estimated market value, those information types will be perceived as more or less uncertain depending on the availability and quality of the information sources.

JOURNAL OF PROPERTY RESEARCH 7

2.3. Second decision: assessment of information

The second decision step in the process is information assessment. Lack of confidence in value judgements is often related to market uncertainty (Tidwell & Gallimore, 2014), and in the appraisal process ‘uncertainty will arise in the valuer’s mind’ (Mallinson & French, 2000, p. 14) due to perceived difficulty in assessing either the market or the individual property in relation to the market. The ability of property appraisers to process available information in a consistent manner is therefore essential (Gallimore, 1996; Joslin, 2005).

Consistency may be equivalent to knowledge of the task. Property appraisers credited by a professional organisation should have the expert knowledge required by the organisation’s statutes. This makes them self-confident and reduces some of their appraisal uncertainty, especially when deciding what type of information and which sources to use. Their expert knowledge includes theoretical knowledge in areas fundamental to commercial property valuation, practical experience and current knowledge of the market (see guidelines, e.g. Royal Institution of Chartered Surveyors (RICS), 2014; for international and UK profes-sionals and Bellman & Lind, 2015, for Swedish professionals).

A requirement of joining the profession includes refusing assignments above the pro-spective professional’s capability or enlisting other experts with the necessary knowledge. Professional appraisers who perceive the information input as difficult to assess because of unreliable information or lack of knowledge can ask for a second opinion from in-house

Figure 2. Information sources and information flows in the appraisal process, developed from the model of levy and schuck (1999).

8 L. BELLMAN

colleagues or other market experts. French and Gabrielli wrote that ‘the degree of the uncertainties will vary according to the level of market activity. The more active a market, the more confidence will be given to the input information’. (2004, p. 484). The estimated market value is always related to uncertainty, as indicated by Lorenz, Trück, and Lützkendorf (2006), who argue that

uncertainty arises due to a lack of knowledge or imperfect information about all the inputs that can be used in an analysis and it is likely that eliminating uncertainty will not be possible since no one will have perfect knowledge about all the circumstances that can impact on the outcome’ (p. 405).

2.4. Market transparency: geographical differences

In their (2005) study of the German property market, Schulte, Rottke and Pitschke’s argue that the concept of transparency is not clearly defined in the literature. A transparent market provides as much information as possible for all market participants, thus minimising infor-mation asymmetry (informational advantages of some market participants over others). To attain a highly transparent property market, it is crucial to ensure that reliable data from different submarkets (e.g. market rents from the rental market or property rents and yields from the investment market) are equally accessible to all participants.

Crosby et al. (2018) argue that mature and transparent commercial property markets such as that in the UK are often regulated by a mix of government legislation and profes-sional institutions. In the UK, appraisal behaviour is monitored by professional bodies such as the Royal Institution of Chartered Surveyors (RICS), which produces guidelines and professional standards for property appraisal. These guidelines and standards state that an appraiser must always act independently and objectively (Royal Institution of Chartered Surveyors [RICS], 2014; as cited in Crosby et al., 2018). In less mature and transparent commercial property markets, professional institutions are not particularly well developed. Crosby et al. (2018) suggest that it is therefore more likely that appraisals in markets with low trading may be biased by client influence, and they question the quality of appraisal-based information in these markets, particularly in regard to estimated market value.

Chen and Yu’s (2009) comparative study of Taiwanese and Singaporean appraisers’ per-ceptions of client influence demonstrated that such influence exists in both countries, and that the most common source of client influence is the clients’ use of their knowledge of market transaction data to affect the valuation. This was especially visible in Taiwan, where market- and property-specific information was less available than in Singapore. In fact, lack of transparency was identified as the main cause of client influence, since clients tend to take advantage of their information power. Moreover, the study showed that most apprais-ers’ confidence in their valuations grew with greater access to information. Chen and Yu (2009) also found that as property appraisers’ local knowledge and experience increased, so too did their confidence and ability to resist client influence. Lim et al. (2006) found differences between the Chinese and Hong Kong territories in the use of information and in appraisal behaviour related to client influence and access to market information. Their study concluded that in terms of client influence there was a greater investment focus on valuation in Hong Kong than in China. In assessing reliable data, there was a large differ-ence between the territories because China, with a relatively new regulatory framework not yet highly transparent and consistent, lacked public registers with accurate, reliable, and

JOURNAL OF PROPERTY RESEARCH 9

comprehensive transaction data. It also seemed more common to use sources from private research or field investigations in Hong Kong.

2.5. Frame of references summary

This section demonstrates that different types of information, such as rental income, con-tractual terms of leases, vacancy rate, location, local environment, conditions and standards, discount rate, residual value, operating and heating costs, maintenance, investment needs, administration and management, and environmental pollution can all have a high or low impact on the property’s estimated market value. In simple terms, appraisers need to make two main decisions to reach an estimated market value.

In the first decision, appraisers need to decide which sources to use for different types of information and how much to rely upon property-specific, market-specific and/or prop-erty owner supplied information. In the second decision, appraisers assess various types of information; their assessment confidence can depend on whether and to what degree they see the information types as reliable, easy to assess and/or in need of two or more opinions.

Appraisers in different market segments in the same country may differ in the informa-tion sources they use and their confidence in assessments based on those sources. These differences may be due to differences between local markets or geographical areas, especially differences in size.

3. Method

3.1. Population and sample

The population of Swedish authorised property appraisers at the time of the study was 138. All these appraisers were invited to participate in the study by email and by letter. After several declined because of parental leave, high workload or other reasons, 67 appraisers participated.

Table 1 shows a male-dominated profession, with men comprising 79% of appraisers in Sweden. The population is also relative old, with 19% born in or before 1949 and a relatively large proportion of those authorised by the year 1994 still active at the time of the study.

Individual background variables of the population were taken from the Samhällsbyggarna’s list of members. The authorised property appraisers who participated in the study were compared with the total population and the study group’s distribution was similar to that of the population, which increases the study’s validity.

Table 1 also shows the respondents’ places of business related to the other background variables. The gender distribution was similar among geographical areas, but there was a higher share of women in Malmoe (31%) than in the other cities. This is probably related to the observation that those in Malmoe are also somewhat younger than the other appraisers and were authorised later.

3.2. Research design and data collection

Structured face-to-face interviews were conducted, and data collected, primarily using the repertory grid technique based on personal construct theory (Kelly, 1955). Personal

10 L. BELLMAN

construct theory suggests that individuals construct their worlds on previous experiences (e.g. educational, professional, etc.) stored in memory. This may be because the human mind uses several systems to construct perceptions of acts, events, people, places, things or objects (Wright & Lam, 2002). Shared experiences among individuals may result in shared or similar perceptions of the world or specific entities (Hofstede, Hofstede, & Minkov, 2010). Kelly (1955) originated the repertory grid technique, which can be used to explain and understand how people, both individually and in groups, perceive the world around them (Gaines & Shaw, 2009, 2010). The first and second steps in gathering data using this technique are selecting elements and eliciting bipolar constructs. The final step is scoring the elements in terms of the constructs (Fransella, Bell, & Bannister, 2004; Jankowicz, 2004) to reveal their relationships. This technique is considered to have high reliability and known to be little influenced by interviewer effects (Wright, 2004).

The repertory grid technique can be used in different ways, depending on the purpose of the study and the population. For example, grid forms can be used on which individuals choose their own elements and constructs (Hisrich & Jankowicz, 1990; Jankowicz & Hisrich, 1987; Wilson, Carter, Tagg, Shaw, & Lam, 2007). Another way, if the population has shared experiences and may construe the world in similar ways, is to use common elements and/or constructs. Common elements and constructs have been used in the property appraisal context (Bellman, Lind, & Öhman, 2016; Bellman & Öhman, 2016) and in contexts such as decision-making by lending officers (Rad, Yazdanfar, & Öhman, 2014), auditor assessments (Öhman, Häckner, Jansson, & Tschudi, 2006), and managers’ and employees’ perceptions of performance appraisal systems (Wright, 2004; Wright & Lam, 2002). The use of common elements and constructs in this study (constructed from previous research and pilot study responses) allowed us to aggregate and analyse the data. The results can also be analysed in different ways, and similar to Greenhalgh and Chapman (1998) and Rad et al. (2014), the grid data in the present study were analysed using a number of statistical methods.

To strengthen the study’s validity and reliability, three informed respondents, who did not participate in the main study, were interviewed in a pilot study. This was done to ensure that the grid form (i.e. the elements and constructs) and the background questions would be perceived as relevant by the respondents in the main study (cf. Jankowicz, 1990, 2004).

Table 1. summary of descriptive statistics (gender, age and year of authorisation) of the population of sweden and the 67 respondents in total and by place of business.

note: there are some rounding errors in the table.

Background variables Place of business

GroupTotal in Sweden

Total of respondent Stockholm

Gothen-burg Malmoe

Other cities

Gender Male 109 (79%) 53 (79%) 15 (75%) 11 (85%) 9 (69%) 18 (86%)female 29 (21%) 14 (21%) 5 (25%) 2 (15%) 4 (31%) 3 (14%)

138 (100%) 67 (100%) 20 (100%) 13 (100%) 13 (100%) 21 (100%)age (year of

birth)<1949 26 (19%) 13 (19%) 3 (15%) 2 (15%) 2 (15%) 6 (29%)1950–1959 37 (27%) 16 (24%) 5 (25%) 4 (31%) 2 (15%) 5 (24%)1960–1969 32 (23%) 20 (30%) 6 (30%) 4 (31%) 4 (31%) 6 (29%)≥1970 43 (31%) 18 (27%) 6 (30%) 3 (23%) 5 (39%) 4 (19%)

138 (100%) 67 (100%) 20 (100%) 13 (100%) 13 (100%) 21 (100%)year of au-

thorisation1994 36 (26%) 19 (28%) 6 (30%) 5 (39%) 2 (15%) 6 (29%)1995–2007 69 (50%) 32 (48%) 10 (50%) 6 (46%) 6 (46%) 10 (48%)2008- 37 (27%) 16 (24%) 4 (20%) 2 (15%) 5 (39%) 5 (24%)

138 (100%) 67 (100%) 20 (100%) 13 (100%) 13 (100%) 21 (100%)

JOURNAL OF PROPERTY RESEARCH 11

Data collection was carried out at the end of 2010 and in 2011 (6 and 61 interviews, respec-tively). It took the respondents in the main study about one to two hours to complete the interview and fill out the grid form.

This study is part of a large Swedish research project using 13 predetermined elements (i.e. information types), based on previous research (e.g. Geltner et al., 2007; Netzell, 2009; Nordlund, 2010) and pilot study interviews. The grid form was based on aspects relevant to an appraisal of a commercial property object for a financial statement. Since the findings of McParland et al. (2002) indicate that it is likely that most authorised Swedish property appraisers use the discounted cash flow method, and both property-specific and market-re-lated data are required when using this method (Nordlund, 2008), several of the elements used in the grid form are related to that specific method. In the end, 13 elements were used in the grid form as follows: (A) vacancy rate, (B) condition and standards, (C) location, (D), maintenance, (E) contractual terms of leases, (F) environmental pollution, (G) administra-tion and management, (H) residual value, (I) local environment, (J) investment needs, (K) discount rate, (L) operating and heating costs, and (M) rental income.

In the overall research project, the grid form consisted of 17 bipolar constructs. This article uses seven of these constructs based on previous property research (Chen & Yu, 2009; French & Gabrielli, 2005; Levy & Schuck, 2005; Nordlund, 2008; Tidwell & Gallimore, 2014): (1) information comes, to a small–large extent, from the property owner, (2) assessment is based, to a small–large extent, on property-specific information, (3) assessment is based, to a small–large extent, on market-specific information, (4) information is slightly–highly reliable, (5) information is difficult–easy to assess, (6) assessment requires many–few second opinions and (7) information has little–major impact on the property’s estimated market value. Each construct is ranked on a 7-point Likert-type scale with endpoints at 1 and 7 (cf. Stewart, Stewart, & Fonda, 1981) and respondents in the main study were asked to indicate their perceptions of each element on the grid form using the scales for the constructs.

3.3. Data analysis

Data from the 67 respondents were analysed stepwise: first at an aggregated level, then at the level of four geographical groups. Descriptive analyses follow the property appraisal process decision steps in Figure 1, starting with the output of the appraisal process (i.e. estimated market value), followed by information sources, and assessment of information.

First, categorical analysis was conducted on the whole sample of respondents’ average scores for the 13 elements (i.e. information types) in the appraisal output (i.e. the impact of the information type on the estimated market value, Construct 7). The information types categorised as having a strong impact on the property’s estimated market value were then analysed further. In this step, as in the following steps, the 7-point scales for the bipolar constructs were divided into three response categories: 1.0–3.0 = low, 3.1–4.9 = moderate and 5.0–7.0 = high.

Information sources were investigated on the scales of ‘property owner’ (Construct 1), ‘property object’ (Construct 2) and ‘property market’ (Construct 3). Information from the property object and the property market can both be categorised as coming from indirect and direct sources, because such information can also come from the property owner. An information source index was constructed from the respondents’ mean scores on Construct 2 (reversed) and Construct 3. The information source index scale ranges 1–7. A high ranking

12 L. BELLMAN

of property object as information source is indicated by 1, and a high ranking of property market as information source is indicated by 7. Since Construct 1 (the property owner) is a mediator of information, it was reported separately, meaning that this construct was not included in the information source index.

Information assessment was investigated on the scales ‘information reliability’ (Construct 4), ‘assessment difficulty’ (Construct 5) and ‘need for second opinions’ (Construct 6). An assessment confidence index was constructed based on the mean scores of the elements of these three constructs. The index scale ranges 1–7, with low confidence indicated by 1 and high confidence by 7.

Geographical differences between the respondents were analysed in two phases according to the location of the respondents’ place of business. Analysis of the four geographical groups (Stockholm, Gothenburg, Malmoe and other cities), was followed by an explicit analysis of the largest market, Stockholm, versus the smallest markets, the ‘other cities’.

A Kruskal–Wallis test was conducted to determine any statistically significant differences due to geographical location. Each high-impact information type’s scores on the informa-tion source index, the property owner (Construct 1), and the assessment confidence index were tested across the four geographical groups. A level of p ≤ .05 was chosen to indicate significant differences across geographical groups. The significant differences were used together with the mean ranks of the geographical groups to decide which market segments (and information types) to analyse further. This resulted in a focus on two geographical groups (Stockholm and ‘other cities’).

A Mann–Whitney U test was conducted to examine significant differences between the largest market (n = 20) and the cities from the smallest markets (n = 21). A Bonferroni adjustment α level of .025 was used to assess statistically significant differences between Stockholm and ‘other cities’. The effect size (r = z/√N) was also calculated as an indicator of significant differences, with .3 indicating a medium effect and .5 a large effect (cf. Cohen, 1988). Only mean scores are reported in this article (even though the two rank tests above compare median scores). Means are normally used when reporting data based on a repertory grid study (e.g. Bellman et al., 2016; Gaines & Shaw, 2009); in this case, they also provide uniform reporting of all data (scales, index, etc).

4. Results and analysis

4.1. Impact on estimated market value

Figure 3 illustrates the high-impact information types on the scale ‘information has little (1) to major (7) impact on the property’s estimated market value’. The right side of the scale shows rental income (6.57), which has by far the highest impact on the market value. Location, discount rate and local environment also have a high impact on market value. All mean scores are shown in Appendix 1.

Overall, four types of information seem to have a particularly high impact on properties’ estimated market values (over 5 on the scale). Accordingly, rental income, location, discount rate and local environment are discussed further in the subsections below.

This paper does not examine why those four information types are perceived as most influential. However, one explanation could be that property appraisers in Sweden pri-marily use discounted cash flow analyses, especially when valuing commercial properties

JOURNAL OF PROPERTY RESEARCH 13

for financial statements (Nordlund, 2008). These four information types are considered income-related and future-oriented, and therefore related to cash flow forecasts and able to affect estimated property market values (cf. Lind & Nordlund, 2014)

4.2. Information sources

The mean scores of the information source index in Figure 4 show whether the high-impact information types are gathered primarily from the property object or the property market. The left side shows information types based more on property-specific information than on market-specific information; the right side shows information types based mainly on market-specific information.

In Figure 4, property appraisers rank the two information sources relatively equally when gathering information on rental income, local environment and location. However, the discount rate (mean 5.34) consists of information gathered mainly from the property market and in this case seems to be the most problematic information type, since property market information can be limited.

Although the Swedish market is relatively transparent, there are opportunities for prop-erty owners to influence valuation by supplying information they consider essential. Figure 5 illustrates that certain information can come mainly from the property owner. As can

Figure 3. summary of mean scores for the 67 respondents regarding the impact of each information type on the property’s estimated market value.

Figure 4.  summary of the mean scores of the information source index for the four high-impact information types.

14 L. BELLMAN

be seen, in contrast to discount rate, location and local environment, rental income scores high on this scale (mean 5.82).

In this case, the most problematic information type is rental income, since it depends on the property owner as a mediator of information. This could be an effect of the lack of public rental information (Englund et al., 2004). The information power that property owners possess over main information sources in the first decision step can be particularly problematic if the owner tries to influence the valuation. This can occur by their consciously or unconsciously withholding information or supplying misinformation (Levy & Schuck, 1999, 2005). Such uncertainty will follow the information flow to the estimated market value (French & Gabrielli, 2005).

The other high-impact information types (location, local environment and discount rate) do not suffer from the indirect mediator effect of client influence because they are gathered more or less directly from the sources. Although discount rate stands out as it consists mainly of information gathered from the property market. In contrast, location, local environment and rental income are gathered from both the property object and the property market.

4.3. Assessment of information

Figure 6 represents the property appraisers’ perceptions of the four high-impact informa-tion types. The left side symbolises low assessment confidence. Remember that the mean value is based on the mean scores of the underlying constructs (i.e. information reliability, difficulty of assessment and need for second opinions).

Figure 5. summary of the mean scores of the four high-impact information types for the information source ‘property owner’.

Figure 6. summary of the mean scores of the assessment confidence index for the four high-impact information types.

JOURNAL OF PROPERTY RESEARCH 15

As can be seen, property appraisers have high confidence when assessing information about location, particularly, and local environment (over 5) in the second decision step. For these two information types, the findings seem consistent with findings from French and Gabrielli (2004), who reported that property appraisers working in a highly transparent market are confident in their assessments. According to the assessment confidence index, property appraisers have moderate confidence when assessing information about rental income and discount rate.

Appraisers have relatively low confidence in assessments of rental income, which may be connected to client pressure in the first decision step. Discount rate is scored close to 3 and perceived as the most problematic type of information to assess. Knowledge and expe-rience of assessing this type of information may not be satisfactory and/or the information may not be perceived as reliable. Related to this, previous research has found systematic overestimation of rental income (Lind & Nordlund, 2014; Öhman et al., 2012).

Lack of knowledge and imperfect information are closely connected to assessment uncer-tainty and lack of appraiser confidence (French & Gabrielli, 2005). One explanation, in line with previous research (Englund et al., 2004; Lind & Lundström, 2009), is that appraisers use standardised assumptions from consulting firms’ reports as explicit property market sources. This indicates that market information may be limited as a main source, even in the highly transparent Swedish property market. According to Tidwell and Gallimore (2014), lack of confidence can be related to market uncertainty, and Chen and Yu (2009) also found that appraisers with less access to information have lower assessment confidence.

4.4. Geographical differences

Overall, the respondents’ perceptions were rather similar over geographical areas. However, there were some significant differences. Table 2 summaries the mean scores for all respond-ents, and the significant differences across the four geographical groups are marked.

As can be seen, the information source index does not show any statistically significant differences across the groups, which indicates that the respondents use about the same combinations of property and market sources. Regarding the property owner, a significant difference (p = .043) holds for discount rate across the groups. This indicates that there are geographical differences, and that some appraisers get this type of information from the property owner more often than others. The assessment confidence index also shows a significant difference (p = .024) according to rental income. Therefore, the two information types, ‘discount rate’ and ‘rental income’, are of interest in relation to geographical differ-ences. For more information about tests of significance across the groups, see Appendix 2.

Table 2. summary of significant differences for the four high-impact information types across the four geographical groups (stockholm, Gothenburg, Malmoe and other cities).

*significant differences across the four different geographical groups, p < .05, retrieved by Kruskal–Wallis test.

Information sources Assessment of information

Information type Information source indexThe property owner as information mediator

Assessment confidence index

Discount rate .394 .043* .341local environment .644 .638 .091location .110 .305 .631rental income .128 .525 .024*

16 L. BELLMAN

Table 3 shows mean scores and summarises the differences in the two information types between the largest market, Stockholm and the smaller markets. For tests of significance between these two groups and their calculated effect sizes, see Appendix 3.

Regarding the information source index, the two groups used property object and property market information similarly, but differed significantly (p = .005) on the role of the property owner as an information mediator. Information about discount rates comes to a small extent from the property owner regardless of geographical location (1.00 for Stockholm and 1.67 for other cities), and the small difference in practice is supported by the calculated medium effect size (.44).

Moreover, while the Stockholm group has moderate confidence in rental income assessment, the group of ‘other cities’ has high confidence in the measure (p = .001). The between-group difference has a large effect size (.51), which indicates a practical difference. Previous research (Englund et al., 2004) has reported more geographical differences than those reported here. For mean scores on each element and construct at the geographical group level, see Appendix 1.

5. Conclusions, implications, limitations and suggestions for further research

Considering the findings for the four high-impact information types, Figure 7 illustrates a revised model of the two decision steps in the property appraisal process (previously illustrated in Figure 1).

The revised model indicates that property appraisers have low or moderate assessment confidence in information sourced from the property market (exemplified by discount rate) or mediated by the property, as exemplified by rental income. These sources result in high or moderate uncertainty in the estimated market values. The findings also indicate that using a nearly equal mix of property object and property market information sources seems a ‘good decision’, at least if the information flow goes directly to the second decision step, bypassing the mediation of the property owners. In this case, appraisers perceive high assessment confidence and low output uncertainty (exemplified by location and local environment).

This model contributes to property appraisal research into the first and second decision steps (i.e. the theory of search and the theory of choice) using different information types. Considering previous research, especially by French and Gabrielli (2005), it can be argued

Table 3. summary of group-level mean scores (stockholm vs. other cities) on decision steps in the ap-praisal process for discount rate and rental income.

*significant differences between the group of stockholm and the group of other cities, Bonferroni adjustment alfa level ≤.025.

Information sourceAssessment of informa-

tion

Information type

Geographi-cal group Information source index

The property owner as information

mediatorAssessment confidence

indexDiscount rate stockholm 5.15 high 1.00* low 3.30 Moderate

other cities 5.55 high 1.67* low 3.73 Moderaterental income stockholm 4.18 Moderate 5.50 high 4.13* Moderate

other cities 3.55 Moderate 5.71 high 5.17* high

JOURNAL OF PROPERTY RESEARCH 17

that perceived uncertainty in the input information in the appraisal process will follow the information flow to the output of the estimated market value. This study highlights that high-impact information types differ from each other and that the first decision in the information gathering stage is critical to the entire process when using only one direct information source or clients as an indirect source. This seems to affect both perceived confidence at the assessment stage and final estimated market value.

The findings reported here indicate some practical implications of the relative impor-tance of decisions made using different information sources. Extended guidelines may help professional property valuers in several ways. They can be made aware of possible unconscious valuation errors arising from using sources without questioning them. Property owners can be particularly doubtful information sources because their self-interest may lead them to provide unreliable information. The singular use of the property market also seems problematic, since it does not include property-specific information. In the worst-case scenario, this can lead to decisions based on a valuation report that is more general and client-influenced than independent and property-specific. In turn, investors may be misled into expecting an unrealistic return on investments.

This study was limited by its small sample of 67 property appraisers surveyed in only one country, and the even smaller sample sizes during the focused study parts in various geographical areas of the country. This may have led to the relatively few geographical differ-ences found here, despite apparent differences in local Swedish markets (cf. Englund et al., 2004) and geographical differences found in research from other countries (Hordijk et al., 2011; Lim et al., 2006) and points to a need for further studies on high-impact information types in various geographical settings.

A related suggestion for future research is to compare different information types and sources used by professional property appraisers, their perceived assessment confidence, and the impact of the outputs in more or less transparent markets. In relation to this, it would also be of interest to investigate appraisers’ perceived client pressure and their perceived uncertainty at different stages in the appraisal process.

Finally, it seems fruitful to examine perceived key risk factors in various markets. For example, in Sweden, unlike in the UK, operational costs are included in total rent, and this affects how NOI is calculated. Such differences may have an impact on results, including assessment confidence in different information types, in various markets.

Figure 7. an updated model of the two decision steps in the property appraisal process and the information flows, including high-impact information types.

18 L. BELLMAN

Disclosure statement

No potential conflict of interest was reported by the author.

Notes on contributor

Lina Bellman is a doctoral student of Business Administration at Mid Sweden University and the Centre for Research on Economic Relations. Her research focuses on behavioural property issues, particularly on property appraisers’ valuations of commercial properties.

ORCID

Lina Bellman   http://orcid.org/0000-0001-7763-0391

References

Amidu, A. R., Aluko, B. T., & Hansz, J. A. (2008). Client feedback pressure and the role of estate surveyors and valuers. Journal of Property Research, 25, 89–106. doi:10.1080/09599910802590982

Baffour Awuah, K. G., & Gyamfi-Yeboah, F. (2017). The role of task complexity in valuation errors analysis in a developing real estate market. Journal of Property Research, 34, 54–76. doi:10.1080/09599916.2017.1315444

Bellman, L., & Lind, H. (2015). Är fastighetsvärderingar att lita på för banker och andra aktörer? [Are property appraisals reliable for banks and other actors?]. In P. Öhman & H. Lundberg (Eds.), Trovärdighet och förtroende i ekonomiska relationer [Credibility and trust in economic relationships] (pp. 75–94). Lund: Studentlitteratur.

Bellman, L., & Öhman, P. (2016). Authorised property appraisers’ perceptions of commercial property valuation. Journal of Property Investment & Finance, 34, 225–248. doi:10.1108/JPIF-08-2015-0061

Bellman, L., Lind, H., & Öhman, P. (2016). How does education from a high-status university affect professional property appraisers’ valuation judgments? Journal of Real Estate Practice and Education, 19, 99–124. Retrieved from http://www.aresjournals.org/doi/abs/10.5555/1521-4842.19.2.99?code=ares-site

Black, R., Brown, G., Diaz, J., Gibler, K., & Grissom, T. (2003). Behavioral research in real estate: A search for the boundaries. Journal of Real Estate Practice and Education, 6, 85–112. Retrieved from http://www.aresjournals.org/doi/abs/10.5555/repe.6.1.r1800212j3885h0 g

Chen, F. Y., & Yu, S. M. (2009). Client influence on valuation: Does language matter?. Journal of Property Investment & Finance, 27, 25–41. doi:10.1108/14635780910926658

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum.Crosby, N., Devaney, S., Lizieri, C., & McAllister, P. (2018). Can institutional investors bias real estate

portfolio appraisals? Evidence from the market downturn. Journal of Business Ethics, 147, 651–667. doi:10.1007/s10551-015-2953-1

Crosby, N., Lizieri, C., & McAllister, P. (2010). Means, motive and opportunity? Disentangling client influence on performance measurement appraisals. Journal of Property Research, 27, 181–201. doi:10.1080/09599916.2010.499014

Cyert, R. M., & March, J. G. (1963). A behavioral theory of the firm. Englewood Cliffs, NJ: Prentice Hall.Diaz, J. (1997). An investigation into the impact of previous expert value estimates on appraisal

judgment. Journal of Real Estate Research, 13, 57–66. Retrieved from http://www.aresjournals.org/doi/abs/10.5555/rees.13.1.5h7232h4q2728341

Diaz, J., III, & Hansz, J. A. (1997). How valuers use the value opinions of others. Journal of Property Valuation and Investment, 15, 256–260. doi:10.1108/14635789710184970

Diaz, J., III, & Hansz, J. A. (2001). The use of reference points in valuation judgment. Journal of Property Research, 18, 141–148. doi:10.1080/09599910110039897

JOURNAL OF PROPERTY RESEARCH 19

Diaz, J., III, & Hansz, A. (2007). Understanding the Behavioural Paradigm in Property Research. Pacific Rim Property Research Journal, 13, 16–34. doi:10.1080/14445921.2007.11104221

Diaz, J., Gallimore, P., & Levy, D. (2002). Residential valuation behaviour in the United States, the United Kingdom and New Zealand. Journal of Property Research, 19, 313–326. doi:10.1080/09599910220008321

Diaz, J., Gallimore, P., & Levy, D. (2004). Multicultural examination of valuation behaviour. Journal of Property Investment & Finance, 22, 339–346. doi:10.1108/14635780410550894

Englund, P., Gunnelin, Å., Hoesli, M., & Soderberg, B. (2004). Implicit forward rents as predictors of future rents. Real Estate Economics, 32, 183–215. doi:10.1111/j.1080-8620.2004.00089.x

Fransella, F., Bell, R., & Bannister, D. (2004). A manual for repertory grid technique (2nd ed.). Chichester: Wiley.

French, N., & Gabrielli, L. (2004). The uncertainty of valuation. Journal of Property Investment & Finance, 22, 484–500. doi:10.1108/14635780410569470

French, N., & Gabrielli, L. (2005). Discounted cash flow: Accounting for uncertainty. Journal of Property Investment & Finance, 23, 75–89. doi:10.1108/14635780510575102

Gaines, B. R., & Shaw, M. L. G. (2009). Rep 5: Conceptual representation software – RepGrid manual for version 1.0. Bedford: C.L. Douglas Centre for Person-Computer Studies.

Gaines, B. R., & Shaw, M. L. G. (2010). Rep 5: Conceptual representation software – Introductory manual for version 1.0. Bedford: C.L. Douglas Centre for Person-Computer Studies.

Gallimore, P. (1996). Confirmation bias in the valuation process: A test for corroborating evidence. Journal of Property Research, 13, 261–273. doi:10.1080/095999196368781

Geltner, D., Miller, N. G., Clayton, J., & Eichholtz, P. (2007). Commercial real estate: Analysis and investments. Mason, OH: Thomson South-Western.

Greenhalgh, L., & Chapman, D. I. (1998). Negotiator relationships: Construct measurement, and demonstration of their impact on the process and outcomes of negotiation. Group Decision and Negotiation, 7, 465–489. doi:10.1023/A:1008694307035

Hisrich, R. D., & Jankowicz, A. D. (1990). Intuition in venture capital decisions: An exploratory study using a new technique. Journal of Business Venturing, 5, 49–62. doi:10.1016/0883-9026(90)90026-P

Hofstede, G., Hofstede, G. J., & Minkov, M. (2010). Cultures and organizations: Software of the mind: Intercultural cooperation and its importance for survival (3rd ed.). New York, NY: McGraw-Hill.

Hordijk, A., Nelisse, P., & Koerhuis-Gritter, L. (2011). European valuation practices: How to compare valuations across borders? Initial findings. Journal of Property Investment & Finance, 29, 575–581. doi:10.1108/14635781111150411

International Valuation Standards Committee. (2013). Building trust in valuation. Retrieved from https://www.ivsc.org

Jankowicz, A. D. (1990). Applications of personal construct psychology in business practice. In G. J. Neimeyer & R. A. Neimeyer (Eds.), Advances in personal construct psychology (Vol. 1, pp. 257–287). Greenwich, CT: JAI.

Jankowicz, D. (2004). The easy guide to the repertory grid. Chichester: Wiley.Jankowicz, D., & Hisrich, R. D. (1987). Intuition in small business lending decisions. Journal of Small

Business Management, 25, 45–52.Jones LaSalle Global Real Estate Transparency Index. (2016) Retrieved from http://www.jll.com/greti/

rankingsJoslin, A. (2005). An investigation into the expression of uncertainty in property valuations. Journal

of Property Investment & Finance, 23, 269–285. doi:10.1108/14635780510599476Kelly, G. A. (1955). The psychology of personal constructs, Vol. 1: A theory of personality. London:

Routledge.Kinnard, W. N., Lenk, M. M., & Worzala, E. M. (1997). Client pressure in the commercial appraisal

industry: How prevalent is it? Journal of Property Valuation and Investment, 15, 233–244. doi:10.1108/14635789710184952

Klamer, P., Bakker, C., & Gruis, V. (2017). Research bias in judgement bias studies – A systematic review of valuation judgement literature. Journal of Property Research, 34, 285–304. doi:10.1080/09599916.2017.1379552

20 L. BELLMAN

Levy, D., & Schuck, E. (1999). The influence of clients on valuations. Journal of Property Investment & Finance, 17, 380–400. doi:10.1108/14635789910271773

Levy, D., & Schuck, E. (2005). The influence of clients on valuations: The clients' perspective. Journal of Property Investment & Finance, 23, 182–201. doi:10.1108/14635780510584364

Lim, L., Adair, A., McGreal, S., & Webb, J. (2006). Strategic management and operations of real estate valuation service providers in Hong Kong. Journal of Property Investment & Finance, 24, 343–362. doi:10.1108/14635780610674525

Lind, H., & Lundström, S. (2009). Kommersiella fastigheter i samhällsbyggandet [Commersial properties in the built environment]. Stockholm: SNS förlag.

Lind, H., & Nordlund, B. (2014). A transparent two-step categorization of valuation methods. Appraisal Journal, 82, 244–251. Retrieved from http://web.b.ebscohost.com

Lorenz, D., Trück, S., & Lützkendorf, T. (2006). Addressing risk and uncertainty in property valuations: A viewpoint from Germany. Journal of Property Investment & Finance, 24, 400–433. doi:10.1108/14635780610691904

Lundström, S. (2005). Fastighetsvärderingar före, under och efter bankkrisen [Property valuations before, during and after the banking crisis]. In N. E. Sandberg (Ed.), Vad kan vi lära av kraschen? Bank- och fastighetskrisen 1990–1993 [What can we learn from the crash? Bank and property crisis 1990–1993] (pp. 189–210). Stockholm: SNS förlag.

Mallinson, M., & French, N. (2000). Uncertainty in property valuation – The nature and relevance of uncertainty and how it might be measured and reported. Journal of Property Investment & Finance, 18, 13–32. doi:10.1108/14635780010316636

McParland, C., Adair, A., & McGreal, S. (2002). Valuation standards: A comparison of four European countries. Journal of Property Investment & Finance, 20, 127–141. doi:10.1108/14635780210420025

Mwasumbi, A. N. (2016). External influence on valuation: Looking for evidence from Tanzania. Journal of Land Administration in Eastern Africa, 2, 224–234. Retrieved from http://journals.aru.ac.tz/index.php/JLAEA/article/view/26

NAI Svefa. (2017). New issue of Swedish Real Estate Market Focus Forest 2017. Retrieved from https://www.naisvefa.se/

Netzell, O. (2009). A study of micro‐level variation in appraisal‐based capitalisation rates. Journal of Property Research, 26, 235–263. doi:10.1080/09599911003669682

Nordlund, B. (2008). Valuation and performance reporting in property companies according to IFRS (Doctoral thesis). Royal Institute of Technology, Stockholm.

Nordlund, B. (2010). Need for disclosure regarding property valuations in financial reports according to IFRS. Journal of Property Investment & Finance, 28, 333–353. doi:10.1108/14635781011069954

Nordlund, B., & Lundström, S. (2011). Kommersiella fastigheter och finansiell stabilitet [Commercial property and financial stability]. In Riksbankens utredning om risker på den svenska bostadsmarknaden [The Riksbank’s Commission of Inquiry into Risks on the Swedish Housing Market] (pp. 365–408). Central bank of Sweden. Retrieved from http://www.riksbank.se/Upload/Rapporter/2011/RUTH/RUTH_kap5.pdf

Nwuba, C. C., Egwuatu, U. S., & Salawu, B. M. (2015). Client influence on valuation: Valuers’ motives to succumb. Journal of Property Research, 32, 147–172. doi:10.1080/09599916.2015.1005117

Öhman, P., Häckner, E., Jansson, A.-M., & Tschudi, F. (2006). Swedish auditors’ view of auditing: Doing things right versus doing the right things. European Accounting Review, 15, 89–114. doi:10.1080/09638180500510475

Öhman, P., Söderberg, B., & Uhlin, O. (2012). Accuracy of Swedish property appraisers’ forecasts of net operating income. Journal of Property Research, 29, 103–122. doi:10.1080/09599916.2011.641997

Rad, A., Yazdanfar, D., & Öhman, P. (2014). Female and male risk aversion. International Journal of Gender and Entrepreneurship, 6, 121–141. doi:10.1108/IJGE-02-2013-0012

Royal Institution of Chartered Surveyors (RICS). (2014). RICS valuation: Professional standards January 2014. London: Royal Institution of Chartered Surveyors. Retrieved from http://www.rics.org/se/knowledge/professional-guidance/redbook

Schulte, K. W., Rottke, N., & Pitschke, C. (2005). Transparency in the German real estate market. Journal of Property Investment & Finance, 23, 90–108. doi:10.1108/14635780510575111

JOURNAL OF PROPERTY RESEARCH 21

Stabell, C. B. (1978). Integrative complexity of information environment perception and information use. An empirical investigation. Organizational Behavior and Human Performance, 22(1), 116–142. doi:10.1016/0030-5073(78)90009-0

Stewart, V., Stewart, A., & Fonda, N. (1981). Business applications of repertory grid. London: McGraw-Hill.

Tidwell, O. A., & Gallimore, P. (2014). The influence of a decision support tool on real estate valuations. Journal of Property Research, 31, 45–63. doi:10.1080/09599916.2013.819519

Wilson, F., Carter, S., Tagg, S., Shaw, E., & Lam, W. (2007). Bank loan officers' perceptions of business owners: The role of gender. British Journal of Management, 18, 154–171. doi:10.1111/j.1467-8551.2006.00508.x

Wright, R. P. (2004). Mapping cognitions to better understand attitudinal and behavioral responses in appraisal research. Journal of Organizational Behavior, 25, 339–374. doi:10.1002/job.245

Wright, R. P., & Lam, S. S. (2002). Comparing apples with apples: The importance of element wording in grid applications. Journal of Constructivist Psychology, 15, 109–119. doi:10.1080/10720530252808692

22 L. BELLMAN

App

endi

x 1.

Mea

n sc

ores

of t

he 6

7 re

spon

dent

s by

geo

grap

hica

l gro

up (S

tock

holm

, Got

henb

urg,

Mal

moe

and

oth

er c

ities

)

A. V

acan

cy

rate

-

B. C

ondi

-tio

n an

d st

and-

ards

- C.

Loc

a-tio

nD

. Mai

nte-

nanc

e

E. C

on-

trac

tual

te

rm o

f le

ases

F. En

vi-

ron-

men

tal

pollu

-tio

n

G.

Adm

. an

d m

an-

age-

men

t

H.

Resi

dual

va

lue

I. Lo

cal

envi

-ro

n-m

ent

J. In

vest

-m

ent

need

s

K. D

is-

coun

t ra

te

L.

Ope

rat-

ing

and

heat

ing

M. R

enta

l in

com

e 1.

Info

rmat

ion

com

es to

a

smal

l (1

)–la

rge

(7)

exte

nt fr

om

the

prop

er-

ty o

wne

r

tota

l4.

933.

521.

724.

136.

663.

904.

521.

392.

244.

491.

315.

245.

82st

ockh

olm

5.15

3.05

1.30

3.95

6.60

4.25

4.45

1.15

1.75

4.55

1.00

5.20

5.50

Got

hen-

burg

5.15

4.08

1.92

4.31

6.69

3.54

4.54

1.46

2.38

4.38

1.23

4.69

6.08

Mal

moe

4.00

3.62

1.62

4.46

6.85

4.15

5.15

1.08

2.08

4.69

1.31

5.77

6.23

oth

er

citie

s5.

143.

572.

054.

006.

573.

624.

191.

762.

714.

381.

675.

295.

71

2.as

sess

men

t is

bas

ed

to a

smal

l (1

)–la

rge

(7)

exte

nt o

n pr

oper

-ty

-spe

cific

in

form

atio

n

tota

l4.

786.

303.

635.

615.

725.

783.

184.

014.

646.

063.

425.

125.

55st

ockh

olm

4.45

6.25

2.80

5.35

5.70

5.75

3.25

4.30

3.90

6.70

3.95

5.35

5.55

Got

hen-

burg

4.85

6.46

2.08

5.77

6.00

6.31

3.85

3.69

4.69

6.38

3.23

5.31

6.15

Mal

moe

4.77

6.15

5.69

5.85

6.00

5.85

2.38

4.46

5.69

5.62

3.54

4.92

5.85

oth

er

citie

s5.

006.

334.

105.

625.

385.

433.

193.

674.

675.

522.

954.

905.

00

3. a

sses

smen

t is

bas

ed

to a

smal

l (1

)–la

rge

(7)

exte

nt o

n m

arke

t-sp

e-ci

fic in

for-

mat

ion

tota

l5.

361.

994.

582.

852.

493.

073.

645.

335.

422.

666.

103.

885.

22st

ockh

olm

5.85

2.00

4.25

3.25

2.50

2.85

3.60

5.45

5.40

3.15

6.25

4.05

5.90

Got

hen-

burg

5.08

2.23

4.23

3.00

2.00

2.46

3.69

5.00

4.69

2.08

6.15

4.00

5.15

Mal

moe

6.00

1.92

4.92

3.08

2.69

3.00

3.46

5.38

5.85

2.31

6.00

3.38

6.08

oth

er

citie

s4.

671.

864.

902.

242.

673.

713.

765.

385.

622.

766.

053.

954.

10

4. In

form

atio

n is

slig

htly

(1

)– h

ighl

y (7

) rel

iabl

e

tota

l4.

394.

726.

484.

016.

132.

393.

702.

675.

703.

573.

854.

545.

75st

ockh

olm

4.15

5.25

6.55

4.45

6.40

3.20

4.10

3.05

5.90

4.00

4.10

4.70

5.65

Got

hen-

burg

4.38

4.62

6.31

3.38

5.77

1.92

3.46

2.31

5.54

3.46

3.15

4.15

5.62

Mal

moe

3.69

4.00

6.54

3.69

6.00

2.23

4.08

2.46

6.00

3.08

3.62

4.69

5.92

oth

er

citie

s5.

054.

716.

484.

196.

192.

003.

242.

675.

433.

524.

194.

525.

81

JOURNAL OF PROPERTY RESEARCH 23

5. D

ifficu

lt (1

)–ea

sy (7

) to

ass

ess

tota

l4.

164.

816.

074.

185.

311.

934.

463.

725.

483.

333.

904.

194.

64st

ockh

olm

4.00

5.05

6.25

4.90

5.30

2.30

5.40

3.10

5.45

3.65

3.30

3.90

3.85

Got

hen-

burg

4.46

4.69

5.62

4.00

5.31

1.46

3.85

3.69

5.08

3.46

4.15

4.62

5.15

Mal

moe

3.85

4.62

6.46

3.46

5.77

1.69

3.85

4.08

5.85

2.77

4.23

3.92

4.54

oth

er

citie

s4.

334.

765.

954.

055.

052.

004.

334.

105.

523.

294.

104.

385.

14

6. a

sses

smen

t re

quire

s m

any

(1)–

few

(7

) sec

ond

opin

ions

tota

l3.

875.

725.

814.

785.

783.

165.

393.

614.

703.

672.

934.

483.

79st

ockh

olm

3.55

5.90

5.70

4.85

6.00

4.20

5.10

3.15

4.50

3.40

2.50

4.30

2.90

Got

hen-

burg

4.46

5.62

6.15

4.62

5.92

2.38

5.69

4.08

5.15

3.31

2.85

4.85

3.92

Mal

moe

3.31

5.23

5.77

4.54

5.15

3.00

5.31

3.77

5.46

3.77

3.69

4.77

3.77

oth

er

citie

s4.

145.

905.

714.

955.

862.

765.

523.

674.

144.

102.

904.

244.

57

7. In

form

atio

n ha

s litt

le

(1)–

maj

or

(7) i

mpa

ct

on th

e pr

oper

ty’s

estim

ated

m

arke

t va

lue

tota

l4.

874.

545.

994.

224.

823.

871.

784.

425.

404.

615.

664.

336.

57st

ockh

olm

4.75

4.25

5.95

3.70

4.75

4.05

1.75

5.00

6.05

4.70

6.05

4.40

6.55

Got

hen-

burg

4.46

4.62

6.38

4.54

5.08

3.85

2.08

3.85

5.08

4.62

6.00

4.46

6.77

Mal

moe

4.77

4.38

5.46

4.31

4.85

4.15

1.85

4.54

5.15

4.77

5.38

4.38

6.46

oth

er

citie

s5.

294.

866.

104.

484.

713.

521.

574.

145.

144.

435.

244.

146.

52

Not

e: E

ach

row

(1–7

) in

the g

rid fo

rm sh

ows t

he se

t of r

atin

gs fo

r a b

ipol

ar co

nstr

uct (

scal

e) b

y th

e mea

ns o

f the

67

resp

onde

nts (

Tota

l) an

d ea

ch g

eogr

aphi

cal

grou

p (S

tock

holm

, Got

henb

urg,

Mal

moe

and

othe

r citi

es, r

espe

ctiv

ely)

. Eac

h co

lum

n sh

ows t

he se

t of r

atin

gs fo

r an

elem

ent (

A–M

). Th

e fou

r inf

orm

atio

n ty

pes

with

the

mos

t im

pact

on

the

estim

ated

mar

ket v

alue

are

indi

cate

d by

cap

ital l

ette

rs.

24 L. BELLMAN

App

endi

x 2.

Sum

mar

y of

Kru

skal

–Wal

lis te

st o

n gr

oup

leve

l (St

ockh

olm

, Got

henb

urg,

Mal

moe

and

oth

er c

ities

)

Info

rmat

ion

type

Geo

grap

hica

l gr

oups

Info

rmat

ion

sour

ce in

dex

The

prop

erty

ow

ner a

s in

form

atio

n m

edia

tor

Ass

essm

ent c

onfid

ence

inde

x

Mea

n ra

nkCh

i-Squ

are

Asy

mp.

Sig

.M

ean

rank

Chi-S

quar

eA

sym

p. S

ig.

Mea

n ra

nkCh

i-Squ

are

Asy

mp.

Sig

.D

isco

unt r

ate

stoc

khol

m29

.68

2.98

1.3

9427

.00

8.12

6.0

4329

.00

3.34

8.3

41G

othe

nbur

g36

.46

34.3

830

.88

Mal

moe

30.4

236

.85

39,6

9o

ther

citi

es38

.81

38.6

737

.17

loca

l env

iron-

men

tst

ockh

olm

38.0

81.

668

.644

29.9

51.

694

.638

33,2

56.

468

.091

Got

henb

urg

30.6

933

.54

33.6

5M

alm

oe30

.65

35.4

645

,23

oth

er c

ities

34.2

437

.24

27.9

8lo

catio

nst

ockh

olm

37.5

06.

039

.110

28.5

03.

621

.305

36,2

31.

728

.631

Got

henb

urg

40.6

238

.85

30.4

2M

alm

oe23

.54

33.5

838

,23

oth

er c

ities

33.0

536

.50

31.4

8re

ntal

inco

me

stoc

khol

m39

.53

5.69

2.1

2830

.58

2.23

6.5

2523

,88

9.41

1.0

24G

othe

nbur

g27

.27

37.2

335

.96

Mal

moe

39.7

338

.92

34,2

3o

ther

citi

es29

.36

32.2

142

.29

Not

e: E

ach

row

show

s the

set o

f mea

n ra

nk, c

hi-s

quar

e and

asym

met

ric si

gnifi

canc

e (A

sym

p. S

ig.)

for a

n in

form

atio

n ty

pe, d

ivid

ed o

f eac

h ge

ogra

phic

al g

roup

(S

tock

holm

, Got

henb

urg,

Mal

moe

and

oth

er c

ities

, res

pect

ivel

y). E

ach

colu

mn

show

s the

set o

f mea

n ra

nk, c

hi-s

quar

e, an

d as

ymm

etric

sign

ifica

nce

for i

nfor

-m

atio

n so

urce

inde

x, th

e pro

pert

y ow

ner a

s inf

orm

atio

n m

edia

tor,

and

asse

ssm

ent c

onfid

ence

inde

x. Th

e tw

o in

form

atio

n ty

pes s

how

ing

signi

fican

t diff

eren

ces

are

high

light

ed b

y bo

ld n

umbe

rs.

JOURNAL OF PROPERTY RESEARCH 25

App

endi

x 3.

Sum

mar

y of

Man

n–W

hitn

ey U

test

bet

wee

n St

ockh

olm

and

oth

er c

ities

Info

rmat

ion

type

Geo

grap

hica

l gr

oups

Mea

n ra

nkSu

m o

f ran

ksM

ann–

Whi

t-ne

y U

Wilc

oxon

WZ

Asy

mp.

sig

.(E

ffect

siz

e)In

form

atio

n so

urce

in

dex

Dis

coun

t rat

est

ockh

olm

18.2

336

4.50

154.

500

364.

500

−1.

467

.142

oth

er c

ities

23.6

449

6.50

rent

al in

com

est

ockh

olm

24.0

848

1.50

148.

500

379.

500

−1.

626

.104

oth

er c

ities

18.0

737

9.50

the

prop

erty

ow

n-er

as i

nfor

mat

ion

med

iato

r

Dis

coun

t rat

est

ockh

olm

17.5

035

0.00

140.

000

350.

000

−2.

788

.005

(.44)

oth

er c

ities

24.3

351

1.00

rent

al in

com

est

ockh

olm

20.3

840

7.50

197.

500

407.

500

−.3

40.7

34o

ther

citi

es21

.60

453.

50as

sess

men

t con

fi-de

nce

inde

xD

isco

unt r

ate

stoc

khol

m18

.18

363.

5015

3.50

036

3.50

0−

1.48

3.1

38o

ther

citi

es23

.69

497.

50re

ntal

inco

me

stoc

khol

m14

.83

296.

5086

.500

296.

500

−3.

237

.001

(.51)

oth

er c

ities

26.8

856

4.50

Not

e: E

ach

row

show

s the

set o

f mea

n ra

nk, s

um o

f ran

ks, M

ann–

Whi

tney

U te

st, W

ilcox

on su

m o

f ran

ks te

st (W

ilcox

on W

), Z,

and

two-

taile

d sig

nific

ance

(A

sym

p. si

g.) f

or o

ne in

form

atio

n ty

pe (i

nfor

mat

ion

sour

ce in

dex,

pro

pert

y ow

ner o

r ass

essm

ent c

onfid

ence

inde

x) b

y geo

grap

hica

l gro

up (S

tock

holm

vers

us o

ther

ci

ties)

. The t

wo

info

rmat

ion

type

s sho

win

g sig

nific

ant d

iffer

ence

s are

hig

hlig

hted

by

bold

num

bers

, and

thei

r cal

cula

ted

effec

t siz

es ar

e rep

orte

d in

par

enth

eses

.